Tight control over glucose levels is crucial for human health. Cells constantly monitor extracellular and cytosolic sugar levels. Acclimation of cellular uptake and release in liver as well as peripheral organs is achieved by changing the kinetic properties of glucose transporters and metabolic enzymes. Our goal is to identify all genes involved in regulating glucose transport, metabolism and compartmentation, and to unravel the flux control networks by fluxomics. The understanding of the networks provides an advanced base for intervention in health-related conditions such as Diabetes, obesity or cancer. Glucose transporters, hexokinases, and enzymes related to glucose and glycogen metabolism are encoded by gene families. The members differ in kinetic properties. We understand large parts of the indirect glucose effect on pancreatic insulin release and the effect of insulin in glucose transporrt activity as a means of inter-organ regulation;less is known about sugar signaling at the cellular basis. Multiparallel sugar signaling cascades control metabolism in yeast;, their interplay is not understood fully yet. This project intends to systematically advance the identification of the signaling networks using fluxomics in yeast and human. The Frommer lab developed genetically encoded FRET sensors for monitoring changes of cytosolic glucose levels. The nanosensors can be used in high-throughput screens to determine flux in genetic variants, i.e. knock-out and siRNA collections. Microfluidic and microplate platforms are developed for static and kinetic screens. The project will systematically identify genes affecting flux components in two models: the unicellular yeast Saccharomyces, and in human HepG2 cells as a model for liver and cancer. Hits identified in the screen will be characterized using FLIP sensors for other sugars, phosphate and by transport and metabolite analyses. The role of the newly identified genes will be compared in different human cell lines including primary hepatocytes. Overexpression and double mutant/double siRNA will enable comparison of sugar signaling networks. This project is relevant for metabolic diseases such as Diabetes and obesity (NIDDK), and due to the importance of sugars for cell proliferation for cancer (NCI), as well as other diseases that arise as a consequence of altered glucose levels. The networks and databases developed in this project promise to provide novel screening methods for novel drugs as well as help identifying new drug targets.